, the students must make an assumption of concentration, with input from the instructor, todetermine the sample sizes for analysis. A microbial seed solution is added to all samples toinsure sufficient biological activity. Blank solutions of seed solution and nutrient water are alsoprepared. The students share data and determine which samples are within the acceptable range(minimum DO or minimum change in DO) to be considered valid. Corrections are made basedon change in DO of blank solutions. In addition to determining the BOD of the sample(s), thestudents conduct a kinetic study and determine the kinetic parameters.This BOD experiment forces students to consider:1) The validity of individual samples2) The need to correct measured DO
Programming CourseBackgroundIn the fall of 2003, Embry-Riddle Aeronautical University formed separate colleges andthe College of Engineering was born. One of the first initiatives of the college was tostrive to have a common first year among all its engineering programs (Aeronautical,Civil, Computer, Electrical, Mechanical, and Software Engineering). Having a commonyear would allow first year engineering students to switch degrees with no impact to theirschedule.One course used by most engineering majors was “CS223 Computer Programming forEngineers” which was originally taught in FORTRAN then migrated to C in the mid90’s. The course taught up to structures in C and was basically a C programming coursetaught by predominantly adjunct professors. The
other six topics that posed problems for students in Spring 2007. Inthe case of arrays and array functions, the majority of examples were modified to include agraphical representation of the array operation(s) being performed, in the hopes that this wouldassist students in understanding what was going on in MATLAB when they performed a givenoperation. In addition, more examples using arrays were included in the lectures succeeding theintroduction of arrays, with the goal of reinforcing student understanding of arrays. For theintroduction of fprintf() and formatted output, examples were revised so that one small featurewas added to each example throughout the lecture. It is hoped that this incremental approach tointroducing fprintf() and
, mathematical, simulated, physical) reflecting all significant aspects of the requirements and constraints• Simulating or testing and analyzing system solution(s) against environmental models• Iterating as necessary to revise the system model or environmental models, or to revise system requirements if too stringent for a viable solution until the design and requirements are fully compatible. Figure 7. System Engineering Method Page 14.735.12Instructors have assigned this project for several years to achieve some of the original outcomesof the course. The major outcome associated with this assignment and assessment includesgetting students to begin to think about how to
semesters of Aliceinstruction included replacing storyboarding with flowcharting. The instructors felt thatflowcharting was a more appropriate algorithm development tool due to the increasinglymathematical nature of the assigned Alice exercises and homework.All of the Alice lessons necessitated the use of laptop computers by the students. Eachclassroom had a teaching assistant who was proficient in Alice programming. Weekly lessons ofAlice involved two parts: (1) lecture containing new programming concept(s) with hands-onexercise (2) continuation of week’s concept with hands-on exercise in the workshop andappropriate homework assignment. Weekly lessons covered the following topics: flowcharting,objects, classes, control structures including
; Witt, E., “Student success in college: Creating conditions that matter”, Washington, D.C.: Association for the Study of Higher Education, 2005.7 Prince, M., “Does Active Learning Work? A Review of the Research”, Journal of Engineering Education, vol. 93, pg. 223–231, 2004.8 Melton, D. Stacking Entrepreneurially Minded Learning Alongside Other Pedagogies, KEENzine, Issue 3, pages 6-9, http://online.fliphtml5.com/zyet/hofr/#p=1.9 Rover, D. T., “New Economy, New Engineer”, Journal of Engineering Education, vol. 94, pg. 427–428, 2005.10 Sarasvathy, S. D., “Effectuation: Elements of entrepreneurial expertise”, London:Edward Elgar Publishing, 2008.11 Halverson, E. R., & Sheridan, K. M
is possible that further analysis will indicate arelationship between the measured constructs and the probability of changing to a non-engineering major.AcknowledgementsThis material is based upon work supported by the National Science Foundation under Grant No. 1712089. Anyopinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and donot necessarily reflect the views of the National Science Foundation.References [1] Stephen R. Porter and Paul D. Umbach. “College Major Choice: An Analysis of Person–environment Fit”. In: Research in Higher Education 47.4 (2006), pp. 429–449. [2] Kerry Meyers et al. “Perspectives on First-Year Engineering Education”. In: age 13 (2008), p. 1. [3
investigating first-year engineering student experiences, faculty experiences, and the connection between the two.Dr. David A. Delaine, Ohio State University Dr. David A. Delaine is an Assistant Professor at The Ohio State University Department of Engineer- ing Education. Within this newly formed department he strives to creatively impact society through investigating the intersections of engineering, education, and social need through research on community engagement and collaborative processes within informal learning. He has obtained a Ph.D. in electrical engineering from Drexel University, in Philadelphia, USA and served as a Postdoctoral Fulbright Scholar at the Escola Polit´ecnica da Universidade de S˜ao Paulo. Dr
], and the Lumina Foundation 's National Tech Challenge selectedEduGuide's intervention as a model for making college access and success more efficient. Theyhave supported EduGuide with a planning grant to further test and refine the platform, as has theW.K. Kellogg Foundation to help scale-up EduGuide’s platform and program.Assessment of Grit Levels of Participating StudentsOverall, 108 freshman-year STEM students participated in the baseline assessment of students’grit levels in early fall 2017. Of the 108 students, 81 were STEMGrow students, while 27 werenon-STEMGrow students (Control Group). The first post-assessment involved 64 students, 43of whom were STEMGrow students, and 21 were non-STEMGrow students. A total of 38students, 26 STEMGrow
Ed.D., West Virginia University Robin A. M. Hensel, Ed.D., is the Assistant Dean for Freshman Experience in the Benjamin M. Statler College of Engineering and Mineral Resources at West Virginia University. While her doctorate is in Curriculum and Instruction, focusing on higher education teaching in STEM fields, she also holds B.S. and M.A. degrees in Mathematics. Dr. Hensel has over seven years of experience working in engineer- ing teams and in project management and administration as a Mathematician and Computer Systems Analyst for the U. S. Department of Energy as well as more than 25 years teaching mathematics, statis- tics, computer science, and freshman engineering courses in higher education institutions
students found to support first-year successCharacteristic Comments (brief)High school academic achievement Indicator of academic preparedness; incoming grades/composite assessmentsQuantitative skills Analytical skills necessary for engineering student successStudy habits Whether student is an independent learner; has experience maintaining regular study habitsCommitment to career and educational goals Early identification of career goal(s
engineering student could be created. Overall, the current data suggest thatfurther research is necessary to determine what other individual differences might be moreeffective predictors of success and retention. As we continue this line of research, we willcontinue investigating additional factors from which persistence in engineering can be predicted.What remains uncontested is the conclusion that better insight into students’ ability to succeedand choice to remain would help educators address the lowering retention rates in engineeringprograms. References[1] S&E Indicators 2016 | NSF - National Science Foundation. National Science Board, National Science Foundation, National Center for Science
: Perceptions of engineers and engineering work amongst domestic and internationalstudents,” Intl. J. First-Year in Higher Educ., vol. 6, no. 1, pp.89-105, March 2015[Bie2016] A.R. Bielefeldt and N.E. Canney, “Humanitarian Aspirations of Engineering Students:Differences between Disciplines and Institutions,” J. Humanitarian Engineering, vol. 4, no. 1,pp. 8-17, 2016[Bra2017] M.M. Bradley, & P.J. Lang, Affective Norms for English Words (ANEW): Instructionmanual and affective ratings. Technical Report C-3. Gainesville, FL: UF Center for the Study ofEmotion and Attention, 2017.[Cav2007] M. Cavalli, L. Stanlake, and S. Tolbert, “Investigation of Retention and Perceptionsamong Freshman Engineering Students”, Proc. 2007 ASEE Midwest Sectional Conference
Proceedings, IEEE Frontiers in Education, 36th Annual Conference, San Diego, CA, October 26 -31, 2006. Session S3G, pp. 1–6. [6] G. Heitmann, “Project-oriented study and project-organized curricula: A brief review of intentions and solutions,” European J. of Engineering Education, vol. 21, no. 2, p. 121-131, 1996. [7] H. Qi and H. Jack, “A scalable course project to accommodate academic variation,” presented at the 2016 ASEE Annual Conference & Exposition, New Orleans, LA, June 26-29, 2016. Paper ID: 15437. [8] K. Meyers, B. P. Conner, and A. S. Morgan, “3-D printing in a first-year engineering design project
in first-year courses to discuss the various majors highlighting similarities and differencesto aid those considering switching. Another option may be connecting first-year students withmore senior students so they can discuss major selection and switching. Through these types ofpractices, we hope to help students select the major that is the best fit.References1. Lichtenstein, G., Loshbaugh, H., Claar, B., Bailey, T., & Sheppard, S. (2007, June). Should I Stay Or Should I Go? Engineering Students' Persistence Is Based On Little Experience Or Data. Paper presented at the ASEE Annual Conference and Exposition, Honolulu, Hawaii. https://peer.asee.org/21772. Arcidiacono, P., Hotz, V. J., & Kang, S. (2012). Modeling college major
requirements, the process for obtaining eachbadge included at least the following: introduction to the new topic (e.g., participation and animpromptu classroom presentation or discussion, hands-on activity in class); reflections on thedesign and development of the project and on their own learning; application of new materials;and finally, the final project itself accompanied by the narrative/reflection and artifact(s). Whilesome projects were to be completed independently, for others, students were encouraged orrequired to work with peers. In addition, some projects could be in part used to meet sub-competencies across multiple badges. Students completed projects on their own timeframe and inthe order they preferred. While there were soft deadlines
Classroom and Beyond: Setting Up Students for Success. Occasional Paper 29, Center for Research on Learning and Teaching, University of Michigan.2 C. Finelli, M. Kendall-Brown. “Using an Interactive Theater Sketch to Improve Students’ Perceptions About and Ability to Function on Diverse Teams.” Proceedings of the 2009 ASEE Annual Conference & Exposition, Austin, TX.3 L. K. Alford, R. Fowler, and S. Sheffield, “Evolution of Student Attitudes Toward Teamwork in a Project-based, Team-based First
and academic achievement in an engineering dynamics course. Global Journal of Engineering Education, 16, 1, 6-12 (2014). Page 26.509.18 17. Kopp, J. P., Zinn, T. E., Finney, S. J., & Jurich, D. P. (2011). The development and evaluation of the Academic Entitlement Questionnaire. Measurement and Evaluation in Counseling and Development, 44(2), 105-129.18. Dweck, C. S. (2006). Mindset: The new psychology of success. New York: Random House LLC.19. Glaser, B., & Strauss, A. (1967). The Discovery of Grounded Theory. Aldine Publishing Company, Hawthorne, NY.20. Charmaz, Kathy (2000). Grounded Theory
not on track for successful completion. Sign in at website to view your Academic Status Report(s). Each class that has a status report will have an orange Academic Status Report icon next to it. Click this icon to view the status report details. Your instructor has noted your current performance level and may have included a reason and recommended actions to help you succeed in this course. Please visit the Academic Status Report Resources Web page at http://students.asu.edu/asrr for information on tutoring, health and wellness resources, and other student support services available to you. Note: The absence of an academic status report for a course does not indicate satisfactory performance in
reflect the views of the National ScienceFoundation.References1. Swail, W.S., Redd, K.E., & Perna, L.W. (2003). Retaining minority students in higher education: A framework for success. ASHE-ERIC Higher Education Report, Adrianna J. Kezar, Series Editor, 30, 2. San Francisco, CA: Jossey-Bass.2. Bairaktarova, D., Reyes, M., Nassr, N., & Carlton D.T. (2015). “Spatial Skills Development of Engineering Students: Identifying Instructional Tools to Incorporate into Existing Curricula,” Proceedings of the 2015 American Society for Engineering Education Annual Conference & Exposition, Seattle, WA, June 14-17, 2015. USA: American Society of Engineering Education.3. Metz, S., Sorby, S., Reap, J., Berry, T., &
with member(s) who had completed themodule and incorporated a microcontroller board into their design was also compared to the restof the class by comparing average final project scores. Final project scores for the RubeGoldberg machines were assigned based on performance, complexity, and professionalappearance. The performance score was based on how well the task was carried out and includedpoints for the precision of the device’s timing and for successfully completing the final step(unlocking the door). Project complexity was assessed by counting the number of different stepsin the process from device activation to the door being unlocked. Finally, projects were expectedto be professional in appearance with the team’s name, logo, and theme
Characteristics to Dimensions of Student Ratings of Teaching Effectiveness,”Coll. Stud. J., 2006.[4] S. Liaw and K.-L. Goh, “Evidence and control of biases in student evaluations ofteaching,” Int. J. Educ. Manag., pp. 37–43, 2003.[5] C. Kim, E. Damewood, and N. Hodge, “Professor Attitude: Its Effect on TeachingEvaluations,” J. Manag. Educ., vol. 24, no. 4, pp. 458–473, 2000.[6] J. S. Pounder, “Is student evaluation of teaching worthwhile? An analyticalframework for answering the question,” Qual. Assur. Educ., 2007.[7] T. Hinkin, “The Effects of Time of Day on Student Teaching Evaluations: Perceptionversus Reality,” J. Mangement Educ., 1991.[8] M. W. Ohland, S. D. Sheppard, G. Lichtenstein, O. Eris, D. Chachra, and R. A. Layton,“Persistence
Wiley & Sons, Ltd., 2012.[3] B.J. Tewksbury, “Specific Strategies for Using the “Jigsaw” Technique for Working in Groups in Non-Lecture-Based Course,” Journal of Geological Education, 43(4), pp. 322- 326, 1995.[4] D. Fitzgerald, “Employing think–pair–share in associate degree nursing curriculum,” Teaching and Learning in Nursing, 8(3), p. 88-90, 2013.[5] D.E. Allen, R.S. Donham, and S.A. Bernhardt, Problem-based learning. New Directions for Teaching and Learning, vol 128, pp. 21-29, 2011.[6] S. Freeman, et al., “Active learning increases student performance in science, engineering, and mathematics.” Proceedings of the National Academy of Sciences of the United States of America, 111(23) pp. 8410-8415, 2014.[7] S. Martin, D
. Research in Higher Education, 46(2), 153-184. 14. Corbin, J., & Strauss, A. (2007). Basics of Qualitative Research: Techniques and Procedures for Developing Grounded Theory. Sage Publications, Incorporated. 15. Cotten, S. R., & Wilson, B. (2006). Student-Faculty Interactions: Dynamics and Determinants. Higher Education: The International Journal of Higher Education and Educational Planning, 51(4), 487-519. 16. Astin
integrating opportunities to develop non-disciplinary workplace related skills into college classes.Dr. Patricia A Ralston, University of Louisville Patricia A. S. Ralston is Professor and Chair of the Department of Engineering Fundamentals at the Uni- versity of Louisville where she also received her B.S., MEng, and Ph.D. degrees in chemical engineering. Her educational research interests include the use of technology in engineering education, incorporation of critical thinking in engineering education, and ways to improve retention. Her other interests include process modeling, simulation, and process control
TestMeasure df t-test p-value Mean diff Cohen’s d2007 Algebra 20 3.62 .0017 10.91 0.52 Trigonometry 20 4.26 .0004 12.10 0.902008 Algebra 11 5.43 .0002 15.50 1.03 Trigonometry 11 4.58 .0008 15.66 1.26Note. Mean diff = Mean difference (post – pre); X post − X pre s 2post + s 2pre Cohen’s d = where s p = sp 2 Page 15.536.7Math Course PlacementTo further assess the Summer Bridge Program with regards
that participated in the survey was substantially lower.This is due to a fairly high attrition rate in the engineering transfer program at our institution.The attrition rate in the first-year engineering program at this institution is ~50%. Regardless ofthis, this research was extremely well received by the students, in an extremely positive way.IV. a) SUMMARY OF THE METHODOLOGIESIt is quite pertinent at this stage to give a brief summary of the MBTI indicator types, and theStrengthsFinder talents/themes and establish a connection between these two assessmentinstruments.The MBTI is based on four dichotomies:E (Extroversion) / I (Introversion)S (Sensing) / N (Intuition
Page 22.1244.13 all students.” • “To a slight degree, it help[s] freshmen succeed and stay in engineering. I've also noticed that I can't think of a single mentor who has not continued in engineering.”Peer mentors’ cumulative grade point averages (GPAs) at the end of the fall 2010 semester wereobtained through the COE to examine academic performance by classification status (see Table11). It is worth noting that students serving as mentors were able to maintain an averagecumulative GPA above 3.0.Table 11Peer Mentors’ Cumulative Grade Point Average Cohort 2007/2008 2008/2009 2009/2010
Design Project mentioned previously. 15The students used a four step process to develop their module: 1. Use of their own experience 2. Formation of design idea(s) 3. Development of predicted behavior based on that idea(s) Page 15.1372.8 4. Testing of the design constructOne of the team members had worked on the Green Campus Enterprise and had participated inwriting the campus wind energy report. 16 Much of their background knowledge of wind energytechnologies came from this report. Other background information came from a 2006 AFG WindEnergy study of the local area. 17 During this preliminary research phase, the students
and speaking improved from this course. I received good feedback onmy work that helped me identify my strengths and weaknesses.” And finally this comment from an email reflection: “This week was a wonderfulexperience for me because I learned how to summarize an article and provide evidence for anargument. I learned that using quotes in my writing can help me back up my thoughts. I loved thereading material from this week because it kept me interested the whole week…I enjoy comingto this class twice a week and I look forward to riding my bike to class. I think you have a funway of relaying important information, and I admire that you want to learn from students.”Bibliography1. Astin, Alexander W. and Astin, Helen S. (1992